Accounts receivable (AR) is a function that spreads across multiple tasks of an enterprise, from corporate finance to sales teams and vendor relationship management initiatives.
Yet AR has widely been viewed as a friction-filled manual task that doesn’t add value to the organization.
Often, even as a function designed to collect payments, AR can even be viewed as a cost center.
Rob Harvey, global director of Solutions Consulting and head of Pre-Sales Operations at order-to-cash automation company Sidetrade, reiterated this sentiment in a recent conversation with PYMNTS.
“Accounts receivable and the management of it within order-to-cash processes has historically felt like the ugly child, or unwanted area within the business,” he said. “It’s a function that crosses frontiers between both sales and finance, with leadership within each function not fully understanding what it is to be a credit controller, and to carry such responsibility for the health and wellbeing of both the business financially, and the day-to-day interactions and relationship the credit department has with its customers.”
That lack of understanding is beginning to shift, however, with more chief financial officers investing in AR technologies that can optimize the process, significantly cut many of the expenses associated with collecting payments, and elevate AR into a strategic function that powers cash flow and deeper customer relationships.
A Legacy Of Outdated Tech
With AR seen as an inconvenient, manual process, many organizations in the past had outsourced the function. Unfortunately, said Harvey, transferring a lackluster process outside of the organization rarely results in an optimized process — and rather, can lead to damaged customer relationships and a lack of deeper insight into key AR metrics like average DSO (Days Sales Outstanding).
The outsourcing trend has slowed, he said, as organizations aim to centralize their operations and begin to understand the potential value in AR.
“CFOs are now looking to the asset side of the balance sheet to drive the next level of improvement,” said Harvey.
The opportunities to improve AR are vast. For instance, Harvey pointed to the dispute resolution process, which is often siloed from the collection process. According to Sidetrade’s own research, about one in every seven invoices involves some kind of dispute, whether linked to missing documents, deductions or otherwise. Further, the research found that a company can spend as long as 74 days on resolving that dispute.
It’s just one example of how a function designed to facilitate capital inflow can actually be an expensive waste of valuable resources.
“This can represent a huge draw on business’s access to working capital, let alone adding further inefficiency and poor customer satisfaction, with multiple touch points throughout the dispute lifecycle across multiple tools and systems,” Harvey said, noting that by streamlining collections and dispute resolution, businesses can strengthen customer relationships and promote “a common culture around cash.”
Digital Disruption Takes Hold
Dispute resolution is a greenfield opportunity for technology like artificial intelligence (AI) to bring major efficiencies into the AR and broader order-to-cash process. According to Harvey, AI is among the most promising tools, as are machine learning (ML) and natural language processing, to optimize AR processes and help organizations take advantage of AR data to unlock insights into metrics like DSO and beyond.
“With ever-growing workloads, siloed functions, systems and teams, the need to make precise, data-driven decisions at the tight time has become a necessity in order to gain a competitive edge,” he said. “The need to access data is becoming more and more imperative as organizations select disruptive cloud technology vendors in order to benefit from their vast data sets.”
Data is at the heart of not only automating much of the manual workload of AR, like chasing unpaid invoices and resolving disputes. It’s also essential to developing a more robust collections strategy based on historical trends in customer payment history, invoicing tactics and more.
Even in the U.S., where paper checks my stifle a business’s ability to seamlessly capture payment data, approaching AR analytics with a focus on customer data supports a predictive approach to developing customer payment forecasts and collection strategies — rather than relying on historical transaction data of invoice payments that have already been settled.
As B2B payments in the U.S. catch up to other markets around the world in digitization adoption, and as faster payment capabilities arm businesses and their service providers with even more robust data to analyze, AR will find itself in an even more strategic position to help businesses build a better collections strategy.
But education must continue to ensure corporates understand the potential to transform AR from a costly, manual process into a value-added operation.
“The market is definitely starting to mature,” said Harvey, “but there will always be a need to educate and provide concrete proof that focusing effort on AR will yield a healthy ROI.”
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